DC pole | Wartość | Język |
dc.contributor.author | Nowak-Brzezińska, Agnieszka | - |
dc.contributor.author | Rybotycki, Tomasz | - |
dc.date.accessioned | 2020-05-06T10:32:32Z | - |
dc.date.available | 2020-05-06T10:32:32Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Schedae Informaticae, Vol. 25 (2016), s. 85-101 | pl_PL |
dc.identifier.issn | 0860-0295 | - |
dc.identifier.issn | 2083-8476 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12128/13851 | - |
dc.description.abstract | In this work the subject of the application of clustering as a knowledge
extraction method from real-world data is discussed. The authors analyze
an influence of different clustering parameters on the quality of the created
structure of rules clusters and the efficiency of the knowledge mining process for
rules / rules clusters. The goal of the experiments was to measure the impact of
clustering parameters on the efficiency of the knowledge mining process in rulebased
knowledge bases denoted by the size of the created clusters or the size
of the representatives. Some parameters guarantee to produce shorter/longer
representatives of the created rules clusters as well as smaller/greater clusters
sizes. | pl_PL |
dc.language.iso | en | pl_PL |
dc.rights | Uznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Polska | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/pl/ | * |
dc.subject | rule-based knowledge bases | pl_PL |
dc.subject | clustering | pl_PL |
dc.subject | similarity | pl_PL |
dc.subject | visualization | pl_PL |
dc.title | Impact of Clustering Parameters on the Efficiency of the Knowledge Mining Process in Rule-based Knowledge Bases | pl_PL |
dc.type | info:eu-repo/semantics/article | pl_PL |
dc.relation.journal | Schedae Informaticae | pl_PL |
dc.identifier.doi | 10.4467/20838476SI.16.007.6188 | - |
Pojawia się w kolekcji: | Artykuły (WNŚiT)
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